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ORCIDVera L. Miguéis
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2020 – today
- 2025
[j17]M. S. Sousa, Ana L. D. Loureiro, Vera L. Miguéis:
Predicting demand for new products in fashion retailing using censored data. Expert Syst. Appl. 259: 125313 (2025)- 2024
- [j16]Inês César, Ivo Pereira
, Fátima Rodrigues, Vera L. Miguéis, Susana Nicola, Ana Madureira, José Luís Reis, José Paulo Marques Dos Santos, Daniel Alves de Oliveira:
A Systematic Review on Responsible Multimodal Sentiment Analysis in Marketing Applications. IEEE Access 12: 111943-111961 (2024) - [j15]João C. Silva, Joel José Puga Coelho Rodrigues, Vera L. Miguéis:
Factors influencing the use of information and communication technologies by students for educational purposes. Educ. Inf. Technol. 29(8): 9313-9353 (2024) - [j14]Miguel Rodrigues, Vera L. Miguéis, Carlos Felix, Carlos Rodrigues:
Machine learning and cointegration for structural health monitoring of a model under environmental effects. Expert Syst. Appl. 238(Part C): 121739 (2024) - 2023
- [j13]Eduardo E. Oliveira, Vera L. Miguéis, José Luís Cabral de Moura Borges:
Automatic root cause analysis in manufacturing: an overview & conceptualization. J. Intell. Manuf. 34(5): 2061-2078 (2023) - 2022
- [j12]Eduardo E. Oliveira, Vera L. Miguéis, José Luís Cabral de Moura Borges:
Understanding Overlap in Automatic Root Cause Analysis in Manufacturing Using Causal Inference. IEEE Access 10: 191-201 (2022) - [j11]Paulo Morais, Vera L. Miguéis, Ivo Pereira:
Leveraging email marketing: Using the subject line to anticipate the open rate. Expert Syst. Appl. 207: 117974 (2022) - [j10]Eduardo E. Oliveira, Vera L. Miguéis, José Luís Cabral de Moura Borges:
On the influence of overlap in automatic root cause analysis in manufacturing. Int. J. Prod. Res. 60(21): 6491-6507 (2022) - [c8]João Neves, Ana L. D. Loureiro, Pedro M. d'Orey, Vera L. Miguéis, Álvaro Costa, Michel Ferreira:
Empirical Evaluation of the Performance of Electric Vehicles for Taxi Operation. VTC Spring 2022: 1-6 - 2020
- [c7]Vera L. Miguéis, Ricardo Teixeira:
Predicting Market Basket Additions as a Way to Enhance Customer Service Levels. IESS 2020: 121-134 - [c6]Jorge Grenha Teixeira, Vera L. Miguéis, Marta Campos Ferreira, Maria Henriqueta Nóvoa, João Falcão e Cunha:
Ten Years Exploring Service Science: Looking Back to Move Forward. IESS 2020: 334-346
2010 – 2019
- 2019
- [j9]Vera L. Miguéis, Ana S. Camanho, João Falcão e Cunha:
Evaluating the short-term effect of cross-market discounts in purchases using neural networks: A case in retail sector. Expert Syst. J. Knowl. Eng. 36(6) (2019) - [c5]Maria P. G. Martins, Vera L. Miguéis, D. S. B. Fonseca, Albano Alves:
A Data Mining Approach for Predicting Academic Success - A Case Study. ICITS 2019: 45-56 - 2018
- [j8]Ana L. D. Loureiro, Vera L. Miguéis, Lucas F. M. da Silva:
Exploring the use of deep neural networks for sales forecasting in fashion retail. Decis. Support Syst. 114: 81-93 (2018) - [j7]Vera L. Miguéis, Ana Freitas, Paulo J. V. Garcia, André Silva:
Early segmentation of students according to their academic performance: A predictive modelling approach. Decis. Support Syst. 115: 36-51 (2018) - 2017
- [c4]Paulo Morais, Vera L. Miguéis, Ana S. Camanho:
Exploring the Relationship Between Corruption and Health Care Services, Education Services and Standard of Living. IESS 2017: 87-100 - [c3]Diogo V. Silva, Vera L. Miguéis:
Combining Data Analytics with Layout Improvement Heuristics to Improve Libraries' Service Quality. IESS 2017: 223-234 - 2016
- [c2]Vera L. Miguéis, Maria Henriqueta Nóvoa:
Using User-Generated Content to Explore Hotel Service Quality Dimensions. IESS 2016: 155-169 - 2013
- [j6]Vera L. Miguéis, Ana S. Camanho, João Falcão e Cunha:
Customer attrition in retailing: An application of Multivariate Adaptive Regression Splines. Expert Syst. Appl. 40(16): 6225-6232 (2013) - [j5]Vera L. Miguéis, Dries F. Benoit, Dirk Van den Poel:
Enhanced decision support in credit scoring using Bayesian binary quantile regression. J. Oper. Res. Soc. 64(9): 1374-1383 (2013) - 2012
- [j4]Vera L. Miguéis, Dirk Van den Poel, Ana S. Camanho, João Falcão e Cunha:
Predicting partial customer churn using Markov for discrimination for modeling first purchase sequences. Adv. Data Anal. Classif. 6(4): 337-353 (2012) - [j3]Vera L. Miguéis, Ana S. Camanho, João Falcão e Cunha:
Customer data mining for lifestyle segmentation. Expert Syst. Appl. 39(10): 9359-9366 (2012) - [j2]Vera L. Miguéis, Dirk Van den Poel, Ana S. Camanho, João Falcão e Cunha:
Modeling partial customer churn: On the value of first product-category purchase sequences. Expert Syst. Appl. 39(12): 11250-11256 (2012) - [j1]Vera L. Miguéis, Ana S. Camanho, Endre Bjørndal, Mette Bjørndal:
Productivity change and innovation in Norwegian electricity distribution companies. J. Oper. Res. Soc. 63(7): 982-990 (2012) - 2011
- [c1]Vera L. Miguéis, Ana S. Camanho, João Falcão e Cunha:
Mining Customer Loyalty Card Programs: The Improvement of Service Levels Enabled by Innovative Segmentation and Promotions Design. IESS 2011: 83-97
Coauthor Index
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